Revision summary
A hypothesis is a testable claim about relations among variables. It guides measurement, sampling, statistical tests and evaluation studies. Mertonian middle-range theory prefers such claims to total systems. Grounded theory and exploratory ethnography warn against premature locking. Bad hypotheses reify official categories and cannot be falsified. Significance is high when the statement can be shown to be wrong.
Model answer
Introduction
A hypothesis is a provisional, testable statement about the relation between two or more variables. It is not a guess thrown into the air, and it is not yet a finding. William Goode and Paul Hatt treated it as the working tool that turns a vague interest into a researchable question. Robert Merton’s middle-range theory lives on hypotheses that can meet evidence, rather than on total systems that explain everything in advance.
Body
Significance in social research
A clear hypothesis names independent and dependent variables, and often the direction of the link: “higher years of women’s schooling are associated with lower completed fertility, controlling for household wealth.” That sentence decides what to measure, whom to sample, and which table or model is relevant. It allows a null hypothesis to be stated and, in quantitative work, statistically assessed. It also disciplines the literature review: one reads to derive and refine the claim, as in Durkheim’s derivations about integration and suicide. In applied work, a hypothesis makes evaluation possible: did a sanitation campaign change reported open defecation, or only slogans?
Critical limits
Not all good sociology begins with a hypothesis. Barney Glaser and Anselm Strauss’s grounded theory builds concepts from data precisely because premature hypotheses can force the field into official boxes. Exploratory ethnography of a new platform labour market may need sensitising concepts, not a locked prediction. A badly theorised hypothesis reifies census categories—“modernisation reduces caste”—and then “confirms” them. Qualitative case studies test hypotheses differently, through pattern matching and deviant cases, not only p-values. Hypotheses can also smuggle values: what counts as “development” is already political.
The critical evaluation is therefore that the hypothesis is indispensable for explanatory and survey research, and dangerous when it becomes a cage. Significance is highest when variables are sociologically real and the statement can be wrong. A hypothesis that cannot fail is not a hypothesis.
Flow diagram
flowchart TD Q[Research question] --> H[Hypothesis] H --> V[Variables] V --> D[Design and sample] D --> E[Evidence] E --> H GT[Grounded theory] -.-> H
Conclusion
A hypothesis states a testable relation and organises measurement, sampling and inference. Its significance is real for scientific sociology. Its limits appear in exploratory and interpretive work, and whenever categories are taken uncritically from the state or from common sense.
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Give a simple example.
“Urban residence is positively associated with later age at marriage among women, controlling for education.”
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